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187 articles for “Fuzzy System”
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Classification of Mammogram Images by Machine Learning Algorithm Attacker Nodes
Abstract: Abstract— Breast cancer is basic in ladies' these days. In beginning when cells in the breast start to develop out of control. These cells generally structure a tumor that will frequently be seen on a x-beam or felt as a lump. Cells in almost any piece of the body can move toward becoming malignant growth and can spread to different regions of the body. There are very nearly 6 phases …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 6, Issue 2, 2019 · pp. 1–10 Read article
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A Review on Two-Wheeled Self-Balancing Robot Using Spartan-3E FPGA for Sensor Fusion and Real-Time Motor Control
Abstract: Two-wheeled self-balancing robots (TWSBR) are a popular application of embedded control and robotics because they operate on the inverted pendulum concept, which is naturally unstable. The main objective of such robots is to continuously maintain balance by estimating the tilt angle and applying corrective motor action in real time. In most practical systems, low-cost inertial sensors such as accelerometers and gyroscopes are used for tilt measurement. However, accelerometer readings are …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 1, 2026 · pp. 17–27 Read article
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Total Quality Management Initiatives for Enhancing the Performance of Manufacturing Companies: An Empirical Investigation
Abstract: Total quality management is the industrial management approach of reducing defects by improving the processes. This study has been carried out in SMEs of northern India which have implemented TQM initiatives and faced different barriers in its successful implementation. Questionnaire survey has been performed followed by Qualitative and Quantitative modeling including interpretive structural modeling, fuzzy set theory, and structural equation modeling. Results of investigation recommended that resistance from employees is …
Published in Journal of Production Research & Management · Vol. 9, Issue 3, 2019 · pp. 41–55 Read article
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Improving Dataset Integrity Through Automated Data Cleaning Techniques
Abstract: High-quality data is a fundamental requirement in data science for producing trustworthy analytical insights and effective machine learning models. Problems, including incomplete records, inconsistent entries, duplicate observations, and anomalous values, can severely reduce the accuracy and robustness of predictive systems. As modern datasets continue to expand in both volume and structural complexity, relying on manual data cleaning methods become time-consuming and error-prone, highlighting the growing importance of automated data preprocessing …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 40–45 Read article
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Segmentation Methods Applied on MR Medical Application
Abstract: AbstractImage segmentation techniques as applied in MRI of human brain are developing by leaps and bounds. The human brain is the most imaging design of the nature. Cancer and neurological problems are resolved using MR of the brain. The automatic diagnostic system starts with medical imaging, segmentation and analysis of the findings and then the final decisions which are further used to treat the patient. In the real world certain …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 3, 2016 · pp. 30–38 Read article
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Efficient Energy Management using Artificial Intelligence (AI) and Machine Learning (ML) in Chemical Industry
Abstract: The globe is moving toward higher usage of renewable energy sources, particularly solar and wind energy, as a result of depleting fossil fuel supplies and growing environmental concerns. There are several forecasting methods available for effective wind energy utilization. This review uses algorithms for predicting solar and wind energy as well as artificial intelligence (AI) techniques. A wind-coal coupling energy system planning scheme was designed to lower the high energy …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 16, Issue 2, 2025 · pp. 33–50 Read article
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Fuzzy C-Means Clustering for Effective Segmentation and Classification of Brain Tumors in MRI Scans
Abstract: The paper discusses the importance of detecting and classifying brain tumors via MRI for effective treatment. It proposes a framework utilizing the Fuzzy C-means clustering algorithm for segmentation, demonstrating improved performance through real dataset validation. The model is trained on a large, annotated MRI dataset to identify and classify different tumor types, enabling machine learning-based classification into benign and malignant tumors. The MATLAB-based solution automates brain tumor feature extraction, aiding …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 23–28 Read article